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Updated: Aug 15, 2026

Using the Race Model Inequality to Quantify Behavioral Multisensory Integration Effects
Published on: May 10, 2019
Conceptualizing and categorizing race and ethnicity in health services research
Marvella E Ford1, P Adam Kelly
1Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, Charleston, SC 29425, USA.
Objectives:
Veterans Affairs (VA) patient populations are becoming increasingly diverse in race and ethnicity. The purpose of this paper is to (1) document the importance of using consistent standards of conceptualizing and categorizing race and ethnicity in health services research, (2) provide an overview of different methods currently used to assess race and ethnicity in health services research, and (3) suggest assessment methods that could be incorporated into health services research to ensure accurate assessment of disease prevalence and incidence, as well as accounts of appropriate health services use, in patients with different racial and ethnic backgrounds.
Design:
A critical review of published literature was used.
Principal Findings:
Race is a complex, multidimensional construct. For some individuals, institutionalized racism and internalized racism are intertwined in the effects of race on health outcomes and health services use. Ethnicity is most commonly used as a social-political construct and includes shared origin, shared language, and shared cultural traditions. Acculturation appears to affect the strength of the relationships among ethnicity, health outcomes, and health services use.
Conclusions:
Improved and consistent methods of data collection need to be developed for use by VA researchers across the country. VA research sites with patients representing specific population groups could use a core set of demographic items in addition to expanded modules designed to assess the ethnic diversity within these population groups. Improved and consistent methods of data collection could result in the collection of higher-quality data, which could lead to the identification of race- and ethnic-specific health services needs. These investigations could in turn lead to the development of interventions designed to reduce or eliminate these disparities.
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